Bushfire CRCResearch Utilisation and knowledge transfer
Erosion in burned catchments of Australia:Regional synthesis and guidelines for evaluating risk
Petter Nyman and Gary J SheridanThe University of MelbourneDecember 2014
Acknowledgements This document is a synthesis that builds upon more than a decade of post-‐fire hydro-‐geomorphic research within the Forest Hydrology Research Group, in the School of Ecosystem and Forest Sciences at The University of Melbourne. We would like to acknowledge and thank our key research sponsors including the Victorian Department of Environment, Land, Water and Planning (DELWP), Melbourne Water, the Australian Research Council, the Bushfire Cooperative Research Centre and the CRC for Forestry. Many thanks also to the many researchers, students and technical staff who have contributed in numerous ways to the data and concepts in this report including Associate Professor Patrick Lane, Dr Christoph Langhans, Dr Hugh Smith, Dr Owen Jones, Dr Jane Cawson, Rene van der Sant, Phillip Noske and Christopher Sherwin. Finally we would like to thank the many staff, partners and stakeholders in the Bushfire CRC who provided valuable feedback during the development of this report. Disclaimer: This document is constructed from consultation and research between Australasian Fire and Emergency Service Authorities Council Limited (AFAC), its member agencies and stakeholders. It is intended to address matters relevant to fire, land management and emergency services across Australia and New Zealand. The information in this document is for general purposes only and is not intended to be used by the general public or untrained persons. Use of this document by AFAC member agencies, organisations and public bodies does not derogate from their statutory obligations. It is important that individuals, agencies, organisations and public bodies make their own enquiries as to the currency of this document and its suitability to their own particular circumstances prior to its use. AFAC does not accept any responsibility for the accuracy, completeness or relevance of this document or the information contained in it, or any liability caused directly or indirectly by any error or omission or actions taken by any person in reliance upon it. Before using this document or the information contained in it you should seek advice from the appropriate fire or emergency services agencies and obtain independent legal advice.
Table of Contents 1 Summary ......................................................................................................................................... 1
2 Project objectives ......................................................................................................................... 3 3 Background .................................................................................................................................... 4
4 Risk models and their applications in land management .............................................. 5
5 Fire, storms and erosion in Australia .................................................................................... 7 5.1 Fire, rainstorms and landforms ........................................................................................... 7
5.2 Wildfire and erosion in Australia: early research (1970 -‐2000) ............................. 9 5.3 Wildfire and erosion in Australia: recent research (2000-‐2012) ......................... 10
5.4 Summary of research ........................................................................................................... 13
5.5 Bushfire CRC research in south eastern Australia – summary recent advances ....................................................................................................................... 15
6 Fire and rainfall regimes as drivers – a regional analysis .......................................... 20 7 Guidelines .................................................................................................................................... 24
8 Recommendation for future research priorities ............................................................ 27
9 References ................................................................................................................................... 29 Appendix 1 ...................................................................................................................................... 34
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1 Summary Predictions of erosion in burned catchments provide land managers with information to carry out post-‐bushfire risk assessments and optimise planned burn operations to minimise potential impacts. The assessment of risk resulting from hydro-‐geomorphic processes can be difficult because of factors such as heterogeneous landscapes and patchy rainfall as well as transient and variable fire effects. There are trade-‐offs between i) the requirements from land management agencies, ii) data availability, and iii) the need to generalise models beyond the exact conditions from which research originated. The impact of fire on catchment properties has been shown to increase erosion rates throughout fire-‐prone regions of Australia. The magnitude of the increase relative to the unburned state is highly variable, ranging from 10-‐1000 times the background levels. Factors such as the nature of the terrain, fire regimes and the frequency of intense rainstorms all contribute to high variability from region to region. The largest documented erosion responses are those in steep terrain of southeast Australia where debris flow processes seem to operate regularly after bushfire. In parts of the Sydney basin, where the impacts of fire on erosion have been studied intensively, the landform associated with the Hawkesbury Sandstone results in low connectivity between hill slopes and rivers. The plateaux, cliffs and gentle foot slopes in this region contrast with the long, steep and uniform slopes of dissected uplands in the Alpine regions of southeast Australia. This potentially causes differences in debris flow potential and post-‐fire erosion response. There is a general lack of knowledge about south and Western Australia. However, the mountain ranges in these two regions typically have lower slopes and are therefore subject to less catchment-‐scale erosion potential. Nevertheless, studies in these regions show that local impacts on erosion can be large, especially where the slopes are steep. There is significant variation in post-‐fire erosion within regions due to factors such as variable soils and variable fire severity. Recent research with the Bushfire Cooperative Research Centre indicates that in southeast Australia the aridity of the landscape can be an important predictor of post-‐fire erosion. The most sensitive catchments are those that are located in dry sclerophyll forests as opposed to those in wet forests. Using an aridity index as a predictor significantly improves the spatial representation of surface runoff from hill slopes in landscapes with variable rainfall and solar exposure. Another study with the Bushfire CRC investigated the relative impacts of planned fire bushfire on erosion in small uniformly burned headwater catchments. The results indicate that planned fire can have significant impacts on erosion, but that these are usually modest compared to the impacts of bushfire. Differences in surface runoff (peak discharge) seemed to drive the differences between low severity and high severity fire. It is unclear how these differences in local erosion rates play out in terms of water quality and sediment transport at larger scales where patchiness within burns, their frequency, their size and their density (burns per area per time) become important.
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The overall exposure of different regions to erosion from burned areas can be evaluated by combining data on fire regimes, rainfall regimes and terrain attributes. Fire and rainfall regimes determine how frequently the landscape is primed for an erosion response. Terrain attributes determine how this ‘priming process’ translates to an erosion response. An evaluation of this exposure to erosion indicates that the research efforts to date largely reflect the varying levels of fire-‐related erosion risk across the Australian landscape. With the exception of Tasmania, the knowledge base is stronger in areas where the potential for fire-‐related erosion is high. Risk assessments provide critical information to minimize impacts of planned burning and to respond to threats associated with post-‐wildfire erosion. A measure of risk can be obtained quantitatively or qualitatively by following a set of generic steps that link the likelihood of a response at a particular location with the potential consequence of that response at a valuable asset. A list of steps is provided (alongside spatial data on topographic erosion potential) to help guide this type of risks assessment.
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2 Project objectives The objective of this project is to develop guidelines for evaluating erosion risk in burned catchments. The guidelines are developed by drawing on recent research on post-‐erosion processes in Australia and New Zealand. The report therefore includes a review/synthesis of post-‐fire erosion research in the Australian/New Zealand region. The synthesis leads to a regional assessment of erosion risk as a result of fire. The regional assessment allows for a preliminary screening of the areas in Australia (and New Zealand) that are most at risk and where the knowledge base is lacking. The synthesis and regional assessment of risk are used in the development of guidelines for i) assessing risk associated with erosion in burned catchments, and ii) monitoring and evaluation of impacts of management interventions. The key questions to be addressed in the guidelines are:
� What are the key relevant Bushfire CRC, and other, research findings and how are these related to geomorphic landscapes of Australia and New Zealand?
� What are the implications for operational applications in fire and land management agencies in Australia and New Zealand?
� What are the limitations (data, process understanding, conceptual analogues, etc.) to quantifying the post fire hydro-‐geomorphic risks across diverse landscape and climate conditions?
The approach to developing the guidelines involves:
� A desk-‐top synthesis of the current knowledge of post-‐fire erosion process in Australia and New Zealand.
� An assessment of the degree to which the existing knowledge base, largely developed following the 2001 Sydney fires and recent Victoria fires (2003-‐2009), can be extended to different geographic and climatic regions.
� Developing qualitative guidelines based on risk factors in particular geomorphic regions to assess risk to water quality.
This is seen as the first phase in an utilisation pathway that has the potential to lead to the development of GIS algorithms and further intensive and specific studies for agencies. Additional research could lead to parameterisation of catchment models to optimise burn scheduling, placement and erosion risk in water supply catchment that are exposed to wildfire.
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3 Background Erosion, flash floods and debris flows are hydro-‐geomorphic processes that intensify due to catchment disturbance by fire. Predictive models of these processes can be and are used by land managers to assess risk to assets, prioritise resources and evaluate trade-‐offs between different management strategies. Assessing risk as a result of hydro-‐geomorphic processes can be difficult because of factors such as heterogeneous landscapes, patchy rainfall, and the transient and variable effects of fire (Nyman et al. 2013a). There are trade-‐offs between i) the requirements from land management agencies, ii) data availability, and iii) the need to generalise models beyond the exact conditions in which the research originated. Recent research with the Bushfire CRC (Fire in the Landscape) has provided new insights into the impacts of prescribed fire and bushfire on catchment processes, although the lack of site-‐specific data across different regions means that the magnitude of impact is unknown for most systems in southeast Australia. The lack of site-‐specific data means that exact predictions of post-‐fire erosion in different fire-‐management regions is generally not feasible. However, our research shows that there are fundamental components of hydro-‐geomorphic processes that can be used to develop a general framework and guidelines for evaluating risk associated with post-‐fire runoff and erosion. Broad guidelines help ensure that the procedures for evaluating risk are consistent with the current knowledge of processes that constitute risk. More specific risk models can be tailored for different geographic regions, with different levels of detail in the risk metrics, depending on data availability and underlying management questions.
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4 Risk models and their applications in land management Risk models vary in the confidence of predictions and they vary in terms of the physical processes that are represented (Nyman et al, 2013a). Suitable approaches for modelling risk depend on the land management issue and the availability of data for a particular catchment or region (Figure 1). Managing risk to water quality in a water supply reservoir, for instance, may require models with accurate predictions of the frequency and magnitude of sediment yields that are produced as a result of fire. Our research team is working towards this type of model as part of an ongoing project with Melbourne Water (Smith et al. 2009). This type of quantitative risk model (situated at the bottom right of figure 1); is parameter intensive and requires a large amount of data to be applied and validated in a particular catchment. In some land management applications, the quantitative approach may result in models that are over-‐parameterised, providing more information than required, and too much detail for effective implementation in existing management procedures. This may be the case during rapid assessment of post-‐wildfire hydro-‐geomorphic risks, where models need to be applied to large areas where data is limited and where there is a need to rapidly identify potential hazards (Department of Environment and Primary Industries, 2013). For this type of application, the level of detail in risk models must be aligned with the type of management setting in which they are used (Sheridan et al, 2011). A set of risk categories (situated at the centre of figure 1), or a qualitative risk model, is therefore more suitable for supporting decision making than the predictions of actual sediment loads at a particular asset. Both types of risk models (quantitative and qualitative) may be needed when planning and managing the potential impacts associated with prescribed burning. In high value catchments (e.g. water supply reservoir), for instance, a catchment manager may want to understand the magnitude of the risk associated with prescribed burning in a critical water supply catchment, in which case the model needs to capture the relation between fire severity and sediment delivery to the reservoir, which is a large undertaking requiring detailed knowledge/data on the conditions in a particular catchment. In other cases, it may be more practical to have simple models that highlight where within the landscape that a burn is most likely to cause erosion with adverse impacts on water quality. This would provide fire managers with the means to mitigate some of the potential impacts. Mitigation can take place before a fire, during planned fire (Russell-‐Smith et al. 2006); through investment in treatment capacity (White et al. 2006); or it can take place after a wildfire in post-‐fire emergency risk assessments (e.g. Sheridan et al. 2009).
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Figure 1. The type of models used for risk assessments vary depending on the management setting (top axis) and the scientific knowledge (left axis) of the underlying hydro-‐geomorphic processes. In an ideal world, all risk assessments would be quantitative, and conducted using site-‐specific erosion models as shown in the bottom right corner of figure 1. However, the application of these models may not be feasible because: i) data may not be available for a particular catchment, or ii) the models are complex, time-‐consuming and difficult to work with, and thus unsuitable for a particular land management setting. The risk assessment approach described in this report is situated toward the middle and upper left of this diagram. The suitability of particular risk models for the different needs of agencies will vary due to a range of factors such as their different management settings and different levels of knowledge. The process of research utilisation across a region may therefore take different trajectories for different agencies. The first step is to identify risk factors through a broad landscape analysis and a review of the erosion literature from the region. This provides an overview of the erosion processes likely to operate in different landforms where topography, vegetation, soil and fire properties vary. This information can be mapped across the landscape according to different geomorphic response units. One example of a geomorphic response unit is the dissected uplands of eastern Victoria, a landform which might extend into to the Snowy Mountains (NSW) and the Namadgi National Park (ACT). Another landform is the scarps and cliffs associated with the Hawkesbury Sandstone in the Nattai Catchments near Sydney. Landform classification provides a basis on which to identify key risk factors and to extrapolate research findings from one region to another. Erosion processes in some landforms may have been studied in detail and risk models for these areas can be devised without much additional research effort. The main challenge is to ensure that models developed for one set of catchment conditions can be transferred and applied in another catchment. Some of the issues regarding the transfer of models from one location to another can be addressed as part of a broad-‐scale analysis of the landscape. However, additional site visits would be required for validation. Other landforms for which there is limited data and, in the case of high value assets, there may be a case for doing more field-‐based research to provide a stronger basis for quantifying risk.
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Figure 1. The type of models used for risk assessments vary depending on the management setting (top axis) and the
scientific knowledge (left axis) of the underlying hydro-geomorphic processes. In an ideal world, all risk assessments
would be quantitative, and conducted using site-specific erosion models shown in bottom right corner of the figure.
However, the application of these models may not be feasible because: i) data may not be available for a particular
catchment, or ii) the models are complex, time-consuming and difficult to work with, and thus unsuitable for a particular
land management setting. The grey box in the figure shows the region of the knowledge-management space that this
report is targeting.
Different management settings (agency needs) and different levels of knowledge means that suitable risk models for a
particular agency will vary. The process of research utilization across a region may therefore take different trajectories for
different agencies. The first step is to identify risk factors through a broad landscape analysis and a review of the erosion
literature from the region. This provides an overview of the erosion processes likely to operate in different landforms
where topography, vegetation, soil and fire properties vary. This information can be mapped across the landscape
according to different geomorphic response units.
One example of a geomorphic response unit is the dissected uplands of eastern Victoria, a landform which might extend
into to the Snowy Mountains (NSW) and the Namadgi National Park (ACT). Another landform is the scarps and cliffs
associated with the Hawkesbury sandstone in the Nattai Catchments near Sydney. Landform classification provides a
basis on which to identify key risk factors and to extrapolate research findings from one region to another. Erosion
processes in some landforms may have been studied in detail and risk models for these areas can be devised without
much additional research effort. The main challenge is to ensure that models developed for one set of catchment
conditions can be transferred and applied in another catchment. Some of the issues regarding the transfer of models
from one location to another can be addressed as part of a broad-scale analysis of the landscape. However, additional
site visits would be required for validation. Other landforms for which there is limited data and, in the case of high value
assets, there may be a case for doing more field-based research to provide a stronger basis for quantifying risk.
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5 Fire, storms and erosion in Australia
5.1 Fire, rainstorms and landforms Fire results in increased erosion because of increases to runoff production and reduced resistance of soil to erosion (Prosser and Williams 1998). Following fire, increases in erosion result in sediment being supplied from hill slopes and headwaters to streams and rivers at higher rates than before the fire. This has implications for water quality (Smith et al. 2011). The role of fire in causing changes to erosion rates and water quality depends on three key factors:
� Fire regime. � Rainfall regime. � Landscape attributes (terrain and soil).
These factors contribute to regional variation in the strength of the interaction between fire and surface processes (Moody et al. 2013; Nyman et al. 2013a). In areas with frequent fire (but very little rainfall), such as semi-‐arid parts of interior Australia, there is likely to be frequent impacts of fire on soil and vegetation, but little impact on water erosion. Low rainfall in these areas may mean that erosion by wind is more important. Conversely, the erosion in a flat area with frequent fires and frequent rainstorms, such as the savannah landscapes of Northern Australia may be relatively insensitive to fire because the low slope gradient results in low stream power. In New Zealand, the relatively low flammability of the forest probably means that fire is not an important control on erosion and sediment transport. The impact of fires on erosion rates is likely to be at a maximum in steep forested areas where i) background erosion rates are low, ii) fire severity is high, ii) where there is high relief and where iv) fire results in large changes to surface runoff. In very broad terms one would expect these to vary with landscape relief (or areas with steep slopes) and the biome (figure 2 a and b). In general, the variable terrain is likely to contribute towards much higher erosion along the Great Dividing Ranges in the east and southeast. In terms of fire regimes, the main regional effect is that some systems, such as tropic al rainforests in Queensland or wet temperate forest in New Zealand, very rarely burn in wildfire. In wet forests of the temperate region in southeast Australia and Tasmania the fire frequency is low but the severity and size of fires can be significant. In Mediterranean–type biomes along the South/Western Australia coast, the dry conditions mean more frequent fire, but because the fuel loads are relatively low, the severity is lower and bushfires are smaller. In the following section, the existing literature on fire and erosion in Australia and New Zealand is synthesised with the aim of 1) identifying the relative importance of fire in controlling erosion rates and 2) assessing the degree to which the existing knowledge base can be used to assess erosion risk in different geographic and climatic regions. The synthesis draws on early research from the south eastern Australia region, as well as more recent studies carried out in response to the large regional bushfires that have burned throughout Canberra, Victoria and NSW over the last decade or so.
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Figure 2. a) Slope (in degrees) calculated from a 90 m Digital Elevation Model (SRTM: http://srtm.csi.cgiar.org/). b) Biomes of Australia (Olson et al. 2001).
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5.2 Wildfire and erosion in Australia: early research (1970 -‐2000) Some of the earliest literature on post-‐fire erosion in Australia dates back to a robust catchment-‐scale study by (Brown 1972) in the Upper Tumut of the Snowy Mountain Region of NSW, which was burned by a ~700 km2 bushfire in 1965. The area consisted of dry Eucalypt forests and some alpine woodland at higher elevation. The study documented substantial increases in sediment loads, as a result of increased sediment availability and overland flow. The maximum sediment concentration in the post-‐fire period was high (120-‐157 gL-‐1) and 1-‐2 orders of magnitude higher than the maximum concentration measured in the decade prior to the bushfire. The majority of the erosion occurred as a result of a few large rainstorms. Within about two years, the sediment concentration had returned towards background values, although surface runoff remained above background levels for more than four years. Another body of literature emerged following a series of bushfires in south eastern Australia between 1979 and 1983. Plot-‐scale studies in Hawkesbury Sandstone catchments in Sydney Basin (NSW) showed that bushfire (moderate severity) has the potential to increase plot-‐scale sediment yield by up to 1000 times the background rate, but that the extent of the increase was strongly dependent on the intensity of rainfall during the post-‐fire window of disturbance (Blong 1982; Atkinson 1984). A later study (Prosser and Williams 1998), conducted within the same geomorphic setting, measured similar responses and reinforced the idea that rainfall is a large source of variation in post-‐fire erosion rates. At the plot scale, the erosion rates on burned hill slopes increased sharply for 30 minute rainfall intensities, I30 > 13 mm h-‐1. In a contrasting geomorphic setting, Leitch et al. (1984) measured the sediment yield from a small and steep headwater catchment in the Central Highlands of Victoria that had been subject to an intense rainfall event (17 mm in less than 1 hour) weeks after bushfire in 1983. The catchment, which is typical of the mountainous regions of eastern Victoria, produced a sediment yield of 22 t ha-‐1 which is equivalent to more than 20 years of background erosion (< 1 t ha-‐1 year-‐1) in these forested systems. The event resulted in 2 900 kg of nitrogen and 220 kg of phosphorus being eroded from hill slopes. In the far-‐east Gippsland region of Victoria, also following bushfires in 1983, a catchment-‐scale (40-‐560 km2) study of water quality indicated that the impacts of wildfire could be substantial with sediment concentrations increasing by up to 2 orders of magnitude (from monthly pre-‐fire peaks of 10 mgL-‐1 to post-‐fire peaks of 1000 mg L-‐1) (Chessman 1986). The majority of the erosion occurred in response to two or three rainstorms within the first few months of the bushfire, with daily rainfall totals between 50 and 100 mm. The erosion was highest in the drier forests where poorly developed soils promoted surface run-‐off and strong peaks in discharge. The deeper, more permeable soils in catchments with wet forests seemed to limit the erosion response, despite the terrain being similar.
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5.3 Wildfire and erosion in Australia: recent research (2000-‐2012) 5.3.1 Hawkesbury Sandstone, Sydney Basin -‐ Dry sclerophyll forests Erosion in the catchments above Lake Burragorang near Sydney following bushfire in 2001 resulted in large sediment yields from hill slopes (5-‐20 t ha-‐1 ) (Shakesby et al. 2003), but most of this sediment was redistributed locally on the slopes and only 1 per cent was delivered to the Nattai River (Tomkins et al. 2007). The relatively subdued impact on sediment transport and water quality in the Nattai River was attributed to i) low connectivity between drainage networks and hill slopes (Blake et al. 2009; Wilkinson et al. 2009) and ii) few high intensity rainstorm following the bushfire (Tomkins et al. 2008). Research following the Sydney bushfires in 2001 indicates that post-‐fire erosion within the Hawkesbury Sandstone in the Sydney Basin is strongly affected by features that are distinctive to that particular geology (Shakesby et al. 2007). Gentle slopes on the plateaux and sandstone cliffs as well as the deep colluvial deposits on foot slopes and valley floor are in many ways unique to Hawkesbury Sandstone and not representative of catchments that characterise a large proportion of Australian uplands (e.g. the Great Dividing Ranges in south eastern Australia, eastern Tasmania and Mt Lofty Ranges in South Australia). 5.3.2 Cotter River catchments, Canberra -‐ Dry sclerophyll forests and sub-‐alpine woodland An intense wildfire in 2003 caused extreme erosion response and large impacts on water quality in the Cotter catchments (White et al. 2006). In the Bendora Dam, where fire-‐related erosion response was most severe, a total of 19 300 tonnes of sediment and 1900 tonnes of organic matter was delivered into the reservoir from upstream catchment (White et al. 2006). The erosion was primarily caused by two intense rainstorms with total rainfall in the range 30-‐50 mm and annual exceedance probabilities of two to five years. The exact intensities are unknown. The effects on water quality in the reservoir were substantial with turbidity exceeding previous maximums by a factor of 30 and with an order of magnitude increase in iron and manganese; ultimately resulting in the construction of a new treatment plant to reduce vulnerability of water supply should similar events occur in the future. Investigations into the frequency of these extreme fire-‐related erosion responses indicate that the last event of similar magnitude occurred about 400 years ago (Worthy and Wasson 2004). 5.3.3 North-‐east Victoria -‐ Wet sclerophyll forests Large bushfires in 2003 affected much of the alpine region in northeast Victoria, NSW, and Canberra. An intensive study on post-‐fire water quality impacts and erosion processes was carried out in wet (Alpine Ash) forests in northeast Victoria (Lane et al. 2006; Sheridan et al. 2007a; Noske et al. 2010; Nyman et al. 2010; Lane et al. 2011). The study showed that the macro porous soil in these wet ecosystems resulted in high infiltration rates and hill slopes that were largely disconnected from the stream network in terms of erosion, even during intense rainfall. Most of the sediment was sourced from within a few metres of the channels. Relative to unburnt conditions there was a nine-‐fold increase in sediment yield in first year after the fire. In terms of total yield, this was relatively low compared to the post-‐fire erosion measured in similar landforms but in drier forest environments (e.g. Leitch et al. 1984; White et al. 2006). However, given that 50 per cent of the sediment was produced during a single storm event, this meant that the maximum sediment concentration was very high within the event (~ 45 000 mg L-‐1) compared to background levels (250 -‐1000 mg L-‐1) (Sheridan et al. 2011).
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5.3.4 Alpine Region, south eastern Australia – Sub-‐alpine woodlands In higher elevation in alpine and sub-‐alpine environments (Snow Gum and Alpine Ash) the effects of wildfire on erosion and water quality are poorly documented. A study of surface lowering of burned and unburned hill slopes by (Smith and Dragovich 2008) showed substantial increase in hill slope erosion as a result of wildfire but that the overall rates of hill slope erosion (3.3 – 26.1 t ha-‐1) were low compared to rates measured in lower elevation dry sclerophyll forests (> 100 t ha-‐1). Data from alpine environment in the Bogong High Plains indicate that fire had significant effects on erosion with monthly post-‐fire sediment fluxes between 135 and 178 g m-‐2, which is equivalent to 1.35 t ha-‐1 per month. While these 11 rates are low compared to post-‐fire erosion rates in steep forested regions of SE Australia, they do represent a risk in terms of land degradation in sensitive alpine environments (Dunkerley et al. 2009). 5.3.5 Eastern Upland of Victoria -‐ Dry sclerophyll forests Adopting a landscape scale approach to quantifying post-‐fire erosion, Nyman et al. (2011) found that water quality impacts following bushfire can, more often than not, be attributed to extreme erosion events that occur in patches where high intensity storm cells overlap with steep terrain, high severity burns in dry forest environments. Reports of mud torrents and flash floods were followed up with detailed surveys which could establish that runoff-‐generated debris flows were the main process by which sediment was transported from hill slopes and headwaters to streams and rivers. The events were triggered by surface run-‐off and widespread sheet erosion on hill slopes in steep headwater catchments. When slurries of ash, sediment and water entered the drainage network, the channel sediment was also eroded, contributing to efficient delivery of sediment first to third order drainage networks. The events described in (Nyman et al. 2011) are similar to the study by (Leitch et al. 1984) and extreme erosion events described in fire-‐prone and mountainous regions elsewhere such as the Mediterranean (García-‐Ruiz et al. 2012) and western US (Cannon et al. 2003). The sediment eroded by these localised debris flows resulted in a large volume of sediment (> 100 t ha-‐1) being released into upland rivers and streams where clay, silt and water quality constituents are transported by rivers to downstream lakes and reservoirs (Sheridan et al. 2007b), posing considerable risk to aquatic ecosystems (Lyon et al. 2008) and water supply (Smith et al. 2011). 5.3.6 Mt Lofty Ranges and Darling Ranges – Dry sclerophyll forest, Jarrah and shrubby woodland At Mt Bold in the Mt Lofty Ranges, South Australia, (Morris et al. 2012) measured a mean surface lowering of ~ 20 mm after a bushfire in steep, rocky and dry shrubby forest catchments. The degree of erosion was strongly dependent on slope gradient (very sharp increase in erosion for slopes greater than 25 degrees). Slope curvature was also important with concave portions of the hill slope being more susceptible to erosion than linear slopes. Most of the erosion took place during an intense rainfall event with annual exceedance probability of ~20%. A study into long-‐term depositional processes in valley-‐fill at the Mt Lofty Ranges (Buckman et al. 2009) indicates that fire events throughout the Holocene (i.e. in the last 6000 years or so) have usually been associated with increased in sediment delivery from hill slopes. So fire in this landscape is likely to be an important control on erosion.
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In the Jarrah Forest of Western Australia, there is not much research on fire and erosion However, observations following a large bushfire in January 2005 indicate that large erosion events can occur in this environment, given high intensity fire and subsequent heavy rainfall. The fire burned through three water supply catchments including some steep sections of the Darkin River catchment which feeds the Mundaring Reservoir and which had high fuel loads due to a long period without fire (Cheney 2010). The impacts on water quality at the reservoir wall were minimal despite some heavy rainfall (44 mm and 72 mm on March 28 and May 19 respectively) (Bartini and Barrett 2007). In the river system, however, and within the upper part of reservoir, there was evidence of some severe erosion, with a total of ~ 1000 m3 of sediment, ash and organic material having to be removed from the stilling pond the Little Darkin Weir. 5.3.7 Eastern Tasmania-‐ Dry sclerophyll forest and shrubby woodland In Tasmania, there has been very little research in post-‐fire erosion and water quality impacts. However, a hill slope experiment (Wilson 1999) on erodible granite near St Helens on the east coast indicates that the effect of fire on erosion can be large even for relatively gentle slopes (15 degrees). The erosion rate was strongly dependent on the stream power (or discharge). Erodibility of the burned slopes was very high, but the relatively high infiltration capacity of was limiting the amount of erosion on the plots. Bursts with rainfall intensity in excess of 50 mm h-‐1 were required to produce substantial surface runoff and erosion. There are studies that provide a longer-‐term perspective on the role of fire in shaping the soils currently mantling the hill slopes in Tasmania (McIntosh et al. 2005; Fletcher et al. 2014). The 12 studies indicate that post-‐fire erosion is an important landscape process leading to distinct spatial-‐temporal patterns of variability in soil physical properties and their nutrient status. 5.3.8 Northern Territory Kakadu region – savannah woodland High intensity rainfall is common in the tropical north at the beginning of the wet season; fires burn the landscape at high rates (almost annually); and the soils can be highly erodible. The combination of these factors may result in fire having an important role in soil erosion, even though the terrain is, in most part, less rugged than the ranges in south eastern Australia. Research indicates that due to the relatively flat terrain, the effect of fires on erosion is low compared to other tropical systems (Townsend and Douglas 2000; Townsend and Douglas 2004). However, significant increases in sediment concentration and water constituents were measured when catchments burned late in the dry season, when intensities were higher than early dry season fires, and when the timing of fire impacts occurred closer to the onset of erosive rainfall. For late season bushfire, the concentration of sediment and other constituents were up by a factor of 10 during episodic run-‐off early in the wet season, while during base flow later in the wet season the concentrations were up by a factor of two to three. Managing fires and promoting fires early in dry season is therefore recommended in terms of reducing erosion and limiting the chance of land degradation and water quality impacts (Russell-‐Smith et al. 2006).
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5.4 Summary of research It is difficult to determine exactly what causes variation in post-‐fire erosion. However an obvious factor is terrain (slope and relief) and variable catchment attributes (soil). Terrain varies depending on geology and history of uplift, denudation and incision. In the Hawkesbury Sandstone the geology seems to be an important factor contributing to low connectivity between hill slopes and the river network. In the Alpine region of Victoria, as well as in Canberra and New South Wales, the high relief and relatively steep slopes seem to correspond with the largest post-‐fire erosion responses. However, the wetter forest types in this region seem to have a somewhat muted response compared to the drier systems, and this is linked to differences in soil properties. Soils vary at small spatial scales and it is difficult to determine how it contributes to variation between regions. One pattern that is emerging from research in central and north eastern Victoria is that forest type (a proxy for water availability) is important and is causing variation in erosion response within the region. A common theme to almost all studies is that the majority of erosion occurs within a very few storm events during which the rainfall intensity is high. This dependency on rainstorms (and its randomness) is a critical factor to consider when modelling erosion and evaluating risk. In the Nattai Catchment near Sydney, the relatively low erosion rate following bushfire in 2001 was attributed to the lack of intense rainfall. And it was argued that this is likely to be a general pattern because of lower than average rainfall during the dry periods when large bushfires are more common. It is unclear, however, if reduced annual rainfall corresponds with reduced frequency of high intensity storms. Catastrophic bushfires in Victoria in 2009 were followed by two years with annual rainfall that was higher than the 10 preceding years. Table 1 summarises the impact of bushfire on erosion relative to unburned erosion rates. The largest recorded responses include the extreme erosion in eastern uplands of Victoria (2003-‐2009), the Cotter Catchments (2003) and those reported by Brown in the upper Tumut in 1972. The most subdued impacts are probably those recorded in the northern territory. Literature on post-‐fire erosion in New Zealand is lacking, possibly reflecting the relatively low importance of fire disturbance on catchment processes in this region (McIntosh et al. 2005), relative to the other geomorphic processes such as landslides and debris flows from flooding rainfall and snowmelt.
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5.5 Bushfire CRC research in south eastern Australia – summary of recent advances 5.5.1 Burned landscapes and erosion: aridity as a predictor Crowning bushfires typically act as a homogenising agent whereby landscape variability due to vegetation diminishes. The landscape is reset and hill slopes are smooth, un-‐vegetated and covered with non-‐cohesive and easily erodible material (Nyman et al. 2013b). This means that the main control on variation in erosion is infiltration capacity. High infiltration capacity reduces surface run-‐off, which is the main agent of erosion and sediment transport. In wet Eucalypt forests of Victoria, for instance, the macro-‐porous soils and high infiltration capacity (> 100 m h-‐1) seems to limit the amount of erosion from burned hill slopes. Dry forests in nearby foothills, however, have lower infiltration capacities (<50 mm h-‐1) resulting in much higher erosion rates. In Victoria, this climatic driven variation in soil infiltration capacity seems to be driving landscape-‐scale variability in erosion. This effect can be seen in data from Aberfeldy fire near the Thompson Reservoir, where post-‐fire run-‐off rates where measured on hill slopes across different levels of aridity (Figure 3). Aridity is the balance between potential evapotranspiration and rainfall (i.e. water availability) and has been quantified for a large area using measures of net radiation and rainfall that represent regional variation as well as local topographic effects (Nyman et al. 2014).
Figure 3. Relationship between peak discharge (m3 h-‐1), rainfall intensity (mm h-‐1) and aridity (-‐) in forests near the Thompson Catchment in Victoria. A simple 2-‐parameter function accounts for 85% of variation. The runoff data was collected for 1 year post-‐fire, at 3 min intervals from 8 m plots, on hill slopes burned by crowning fire during the Aberfeldy fire in February 2013. Data (unpublished) from Rene van der Sant, PhD student with the Bushfire CRC/University of Melbourne.
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The relationship in Figure 3 indicates that the aridity index (or long term ratio between potential evapotranspiration and rainfall) can be a very strong predictor of erosion potential in landscapes where aridity (or dryness) results in climatic-‐related variation in soil properties. In the eastern uplands of Victoria, where the role of aridity is beginning to be quantified, the aridity index varies from ~0.8 to 4.5. This range includes biomes ranging from rainforest to open woodland. Surface run-‐off is very sensitive to changes in aridity between 1 and 2. It remains unknown how important aridity is as predictor for drier landscapes (e.g. South Australia) where aridity is generally higher than~ 3. 5.5.2 Fire severity: Bushfire versus planned fire In mixed severity and understory burns, fire severity can have large effects on erosion from burned areas, because of i) patchiness in the fire footprint, and ii) less combustion and soil heating within burned patches. Burn patchiness and its effects on hydrological processes is difficult to model and quantity. In a bushfire setting, the fire severity is typically classified into categories; understory burn (>3), crown scorch (2) and crown burn (1). These categories are usually obtained from some continuous metric such as normalized burn ratio (dNBR) from remotely sensed data (e.g. spot or Landsat imagery) which quantifies the amount of biomass lost in the burn. These continuous metrics are more suited to hydrological modelling because of the representation of spatial pattern in gridded data. For mixed severity and understorey burns (particularly planned fire) it seems that runoff and erosion processes can be insensitive to subtle variations in fire severity and that it is the patchiness in burns that are important (Moody et al. 2008; Cawson et al. 2013). In quantifying the effects of fire severity on erosion, the fire severity metric is therefore better represented as a continuous grid-‐based metric (e.g. dNBR or NDVI) (Chafer 2008) rather than polygons with fire severity categories. The synthesis of literature in Section 4.2 considers the effects of bushfire on erosion. Bushfires represent a very different type of impact compared to planned (or prescribed) fire, particularly in high rainfall regions where background fuel loads are high and where bushfires burn with very high intensity (Cawson et al. 2012). Differences in erosion after bushfire versus planned fire can be attributed to i) the degree of soil heating (DeBano 2000), ii) the degree of patchiness of vegetation after burning (Cawson et al. 2013) , and iii) the timing of the burn in relation to seasonal rainfall patterns (Russell-‐Smith et al. 2006). In a review of surface runoff and erosion after prescribed burning Cawson et al. (2012) found that the impacts on catchment scale erosion were usually minimal, but that very large erosion events do occur in instances when burns are followed by high intensity rainfall. Factors contributing to the relatively subdued erosion response of planned fires include i) low fire severity, ii) burn patchiness, iii) intact riparian vegetation and dilution as a result of small burned areas relative to the overall catchment area. In a study on the effects of burn patchiness on sediment flux on 100 m long hill slopes (~ 25 degrees) near the Upper Yarra catchment (Cawson et al. 2013) found that in the first 16-‐months after fire, a uniform prescribed burn increased the annual sediment flux by up to 3 order of magnitude (from 1.3 g m-‐1 yr-‐1 for unburnt hill slopes to ~1300 g m-‐1 yr-‐1 for burned hill slopes), although they found that this response was very sensitive to: Post-‐fire rainfall: A single event (I15 ~54 mm h-‐1) produced 80% of the total sediment flux. The I15 had an average return interval of ~ 4 years, while the I30 had a return interval of 8-‐10 years. It is unclear which is the right temporal scale for causing the hill slope erosion response although usually it is the short rainfall bursts within the storm that cause most of the erosion. The degree of patchiness in the burn. Unburnt buffers (or patches) of widths 1, 5, and 10 m resulted in a reduction on sediment flux of 1.3, 98.1 and 99.9%, respectively.
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A recent study with the Bushfire CRC into the effects of planned fires versus bushfire near Myrtleford in north east Victoria indicates that erosion processes in small headwater catchments (~ 0.3 ha) can be strongly affected by prescribed fire, but that the effects are substantially lower the when compared to the response after the catastrophic 2009 bushfires (Figure 4). For bushfire affected headwater (crown burn), the run-‐off increased non-‐linearly with a sharp increase for rainfall intensities 10 mm h-‐1, whereas in lower severity planned burns (scorch height of 1-‐8 m), there seems to be a threshold rainfall intensity around 30-‐40 mm h-‐1 below which the runoff response is unlikely to cause much erosion. This threshold intensity seems consistent with the results from Cawson et al. (2013).
Figure 4. Peak discharge for bushfire and planned fire as a function of rainfall intensity. This metric of peak discharge is directly related to the capacity of the catchment to erode and transport sediment. The data (unpublished) was collected as part of a research project partially funded by the Bushfire CRC. Result from this work is being prepared for publication and is yet to undergo peer-‐review. The peak discharge per unit area varied predictably with rainfall intensity, but the relation was dependent on the type of disturbance. As expected, the unburnt catchment produced very little runoff, even for rainfall intensities of ~ 40 mm h-‐1. The bushfire-‐affected catchment produced largest peak discharge. Extrapolating the curve to obtain the peak discharge for debris flow producing storms in this region (I15 ≈ 40 mm h-‐1: return interval of < 1 year) (see: Nyman 2013) indicates that debris flow events correspond with peak discharge of ~ 350 m3 ha-‐1 hr-‐1. The trends for the planned burn in Figure 5 indicate that an I15 of ~60 mm h-‐1 (return interval of ~ 3 years in this region) would be required to produce the same runoff response from a planned burn. Whether or not such an event would result in large debris flow depends on the burn pattern more broadly across the catchment; a single headwater of this size (<1 ha) is unlikely to be sufficient for sustaining debris flow processes at larger scales. The picture in Figure 5 b shows how the transport of sediment and organic matter resulted in equipment failure in the instrumented planned burn following a moderately intense rainfall event (I15 = 20 mm h-‐1).
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Figure 5. Instrumented headwater catchments in north-‐east Victoria. a) The sediment trap and tipping bucket after installation in a prescribed burn. b) The first storm event after the burn (I15 = 20 mm h-‐1; Average return interval =1) resulted in 450 kg (2.5 t ha-‐1) of erosion. This event carried a lot of large organic debris which exceeded the measurement capacity of the equipment.
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5.5.3 Rainfall, bushfire regimes and episodic patches of erosion Almost all catchments are likely to respond with some increase in erosion as a result of vegetation removal by fire. A recurring theme, however, in the Australian and international literature on post-‐fire erosion is that most of the erosion occurs as a result of a few large (or extreme) erosion responses (Brown 1972; Miller et al. 2003; White et al. 2006;Nyman et al. 2011). The magnitude of the threat to water supply or other water resources assets (e.g. biodiversity or recreation) is therefore not embedded within the average erosion response from burned areas. Instead it is a function of the likelihood (or probability) of erosion response exceeding some threshold. Thresholds may be the treatment capacity of a water supply system, tolerable sediment concentration for a fish species or a phosphorous threshold for blue-‐green algae blooms. This likelihood of erosion exceeding a tolerable threshold is determined by the terrain, soil and the spatial-‐temporal pattern of fire events and rainstorms which prime the landscape for a response (Nyman et al. 2013a). The role of fire and rainfall in cause variation in risk was modelled by Jones et al. (2014) using a spatial-‐temporal model (Figure 6) which represents the frequency and the area of overlapping burned areas and rain storms. This type of modelling approach can be coupled with information on landscape properties (soil and terrain) to quantify the likelihood of fires and rainfall resulting in adverse impacts on water quality.
Figure 6. A single realisation of rain storms and burn impacts in space (1000 km x 1000 km) and time (50 years). For burn impacts in this hypothetical scenario the mean radius of the disc shaped burn areas is 100 km, the duration of impact is 2 years and the average return interval for bushfires is 20 years. The corresponding values for rain storms are 1 km, 30 minutes and 2 years. The risk set, where rain storm and burn impacts overlap, is where erosion events may occur (reproduced from Jones et al, 2014)
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6 Fire and rainfall regimes as drivers – a regional analysis This section describes an approach for regional assessment of risk associated with fire and rain storms in catchments. The assessment uses fire history and design storms to obtain a measure of the degree to which a landscape is primed by fire and intense rainfall (see section 1.5.3 and Figure 6). The analysis builds on the methods developed in Jones et al. (2014) and defines the following parameters to describe the fire and rainfall regime of a region:
� λ = fire event rate (km-‐2 year-‐1) � μ = storm event rate (km-‐2 year-‐1) � α = E||fire event|| (km2 × years) � β = E||rainfall event|| (km2 × years)
These parameters are used to obtain 𝐸‖𝐴, which is the average annual rate of intersection between storms and rainfall (or the index of fire and storm overlap). This is the rate at which the landscape is primed by fire events and rain storms; in each of the major capitals of Australia. Auckland, New Zealand, was initially included in the analysis, but with no fires between 1991 and 2007 on the North Island exceeding 150 ha in size (Anderson et al. 2008), the importance of burning on catchment processes was assumed negligible. Fire history was obtained from different sources (Table 2). For some jurisdictions, fire history was provided by local agencies. In other cases, data was located through online databases.
Topographic effects on erosion potential for headwaters (areas < 250 ha) was calculated across Australia and New Zealand using a 90 m DEM available from the Shuttle Radar Topography Mission SRTM (http://www.cgiarcsi.org/data/srtm-‐90m-‐digital-‐elevation-‐database-‐v4-‐1). The equation is based on the LS factor (known as the topographic erosion potential) in the RUSLE model (Renard et al. 1991) but modified (see: Desmet and Govers 1996) to incorporate information on convergent hill slopes in its representation of erosion risk:
A is the contributing area (m2), S is the slope (degrees) and m and n are parameters (0.5 and 1.3, respectively) that describes the relative importance of slope gradient versus contributing area.
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Table 2. Some high-value catchment and the cities they supply. Catchment are partially of fully forested.
City Water supply catchments Reservoirs Capacity (GL)
AEP % I30 = 35 mm h-1
Mean LS
Duration of fire record
Forest area
km2
Mean fire size km2
Fire frequency
year-1 km-2 E||A||
Sydney
Shoalhaven Lake Yarrunga 8
63 10.8 1962 - 2014 28 106 97 2.16 7.4 Upper Nepean Lake Napean 68
Warragamba Lake Burragorang 2027
Canberra Cotter River Catchment
Corin 71
34 19.3 1938 - 2014 7 640 96 1.76 3.3 - 6.0 Bundoora 11
Cotter 76
Perth Darling Ranges Helena River Reservoir 64
24 3.1 2003 - 2013 9 160 78 1.59 1.7 - 4.4
Canning Reservoir 90
Adelaide Mt Lofty Ranges Mt Bold Reservoir 46
14 4.1 1931 - 2014 6 219 78 1.51 0.9 - 4.2 Kangaroo Ck 19
Melbourne Yarra Ranges Upper Yarra Reservoir 201
24 18.7 1927 - 2012 64 020 95 1.73 2.2 Baw Baw / Thompson Thompson Reservoir 1070
Hobart Mt Wellington Wellington Park n/a 6 22.9 1980 - 2013 47 860 58 0.84 0.17 - 1.7
Darwin Darwin River Darwin River Dam 285 63 0.7 - - - - 622
Brisbane D'Aguilar Range Somerset Dam 378
63 15.3 1986 - 2013 46 217 28 0.22 0.2 Wivenhoe Dam 1165
Auckland Hunua Ranges Mangatangi Dam 35
36 12.3 1991 - 2007 - - - 0 Waitakere Ranges
Lower Huia Dam 6
1The storm frequency is calculated for 30-minute storms with intensities ranging from 20 – 35 mm h-1. The maximum storm frequency is when storms on average occur at least once a year. 2 The fire regime parameters from Darwin were calculated based on the average annual proportion of land burned (~19%) (Russell-Smith et al. 2006).
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The mean LS (eq. 2) were calculated for individual catchments contributing to the water supply reservoirs. In most cases the LS were consistent for all the catchments although the Warragamba catchment near Sydney had very different values in the southern arm (LS=9) versus the northern arm (LS = 15). Figure 7 shows the how LS varies in Australia with a clear tendency for higher values in the Dividing Ranges along the east and south-‐east coast. Maps of the LS factor for different water supply catchments of major cities in Table 2 are shown Appendix 1. These provide some examples that are representative of some of the different regions. However, there are many other important reservoirs in cities and regional towns that are not included.
Figure 7 Variation in topographic erosion potential (LS) across the Australian continent. Terrain along the eastern and south-‐eastern coast stands out with the highest potential for erosion. The combined effects of LS and 𝐸‖𝐴‖ on erosion risk is shown in a two dimensional plot which describes the regional exposure to risk. The y-‐axis (storm and fire overlaps) can be interpreted as the likelihood of coincidence of forcing variables, while the topographic erosion potential is the consequence. Catchment near Darwin frequently burn and they experience intense thunderstorm activity, hence the likelihood of fire and storm overlaps is very high (Figure 8). The terrain is flat so the consequence of overlaps is low. In Hobart, the storm frequency is low and fires are generally smaller, so the likelihood of overlaps is low to moderate, depending on the rainfall intensity threshold. The consequence is very high due to the steep slopes of Mt Wellington which forms much of the water supply network in Wellington Park. Canberra and Melbourne are very similar with moderate likelihood but high consequence, which is consistent with observation. New Zealand did not make it onto the chart because the fire and storm overlap was negligible (~0). Water supply catchments in the Mt Lofty Ranges (Adelaide) and those in the Darling Ranges (Perth) form a pair at the lower end of the consequence-‐axis (x-‐axis) and with low to moderate likelihood (y-‐axis).
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Figure 8. Topographic erosion potential a) Matrix for evaluating exposure to risk from bushfire-‐related erosion in forested catchments. In b)Darwin is excluded because of the distinctiveness of the tropical region in terms of fire and rainfall regimes. The LS factor (x-‐axis) represents the topographic erosion potential while the 𝐸 𝐴‖ metric (y-‐axis) represents the intensity of the fire and storm processes leading to erosion. The y-‐axis can be interpreted as the likelihood of the landscape being primed by rainfall and burns. The x-‐axis is the potential erosion response (or consequence) of this priming process. 𝐸‖𝐴‖ on the y-‐axis is displayed as a range for some sites because it incorporates the varying levels of overlap depending on the 30-‐minute storm intensity threshold used in the model. The model currently includes 30-‐minute intensities between 20 and 35 mm h-‐1. On average, in the water supply catchments of Darwin, Brisbane and Sydney these storms occur at least once a year. The 𝐸‖𝐴‖ in these regions is therefore insensitive to changes in the storm threshold; hence it is a single value. At the other sites the 35 mm h-‐1 storm had a recurrence interval of more than a year so reducing the threshold meant that 𝐸‖𝐴‖ also increased. At 20 mm h-‐1 the storms occur on an annual basis everywhere, and there is no further increase in 𝐸‖𝐴‖. Low, moderate and high categories are arbitrary and were defined simply by dividing the risk into three equally spaced categories. Note that the Sydney catchments include a very large area and that there are sections within these areas that have higher LS than the average values in this figure.
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7 Guidelines This section of the report describes guidelines or a set of steps for assessing erosion risk. The steps lead to an estimation of risk. The framework is general, allowing for different management settings which may vary in terms of data availability, type of assets, potential consequences and the available options for mitigating the risk. The steps are similar whether risk assessment is part of planned fire operations, strategic planning (pre-‐fire) or a rapid post-‐fire response operation. 7.1 Six generic steps for risk assessment 1. Identify relevant assets. Assets vary depending on location and management setting, but are typically associated with off-‐site (i.e. downstream) impacts, although they can also be local (e.g. when the concerns relate to impacts on soil resources). Assets include:
� Water reservoirs and water off-‐take points. � Culverts, roads and other infrastructure that may be impacted by flash floods or debris flows. � Biodiversity (fish, invertebrates, ecosystem function). � Recreational assets (picnic grounds, campsites, swimming holes.). � Soil resources (nutrient status, organic matter).
2. Locate relevant assets and determine their vulnerability to impacts of erosion. Vulnerability may for instance be a function of treatment capacity in a water supply system or the sensitivity of an invertebrate to turbid water. Consider factors such as whether:
� The asset may be a water off-‐take in a river, in which case the contributing area may be very large catchments. At this scale the catchment may be partially burned by bushfire or it may have multiple planned burns scheduled in it over a fire season.
� The asset may be a small population of a threatened fish species, in which case the contributing area may be relatively small and embedded entirely within a burned area.
� The asset’s vulnerability to erosion/water quality impacts. Understanding the vulnerability is critical because it helps identity the relevant variables for evaluating risk and monitoring impacts. For some assets, such as water supply reservoirs, the vulnerability is typically linked to peak concentrations of sediment (or some other constituent).
� Ecological assets may also be vulnerable to cumulative low-‐level but reoccurring water quality impacts, such as the combined effects of small planned burn areas within a larger catchment.
3. Determine the potential exposure to risk by identifying the processes that are likely to operate. Both the type and intensity of process are relevant.
� Use past observation or available knowledge from a representative region to determine what type of processes is likely to operate. Landslides, debris flows, sheet erosion, gully erosion are different processes that should be identified as separate sources of risk.
� If there is no relevant literature for a particular catchment then work off simple erosion models such as RUSLE (e.g. Rulli et al. 2013).
� Determine the potential erosion response (including the worst case scenario in terms of impact on assets) given the type of processes operating in a particular setting. How do these compare to background levels (i.e. is there a substantial change relative to background exposure).
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� Assets that are located a long distance downstream from a burned catchment may be less exposed to impacts than assets located within or nearby the burned catchments. The attenuating of exposure with distance from erosion source can be done qualitatively by weighting the importance of the source area (burned catchment) based on its distance from the asset (see equation 3 in Weidner and Todd 2011).
4. Determine the consequence of erosion processes.
� What is the potential consequence given the erosion responses (from 3) and vulnerability of the asset to erosion (from 2 above)?
� The consequence can be interruptions to water supply (treatment capacity exceeded), local loss of biodiversity or persistent changes in stream function. In engineering design and water supply systems, the consequences can be easily determined by examining the vulnerability of the systems to erosion.
5. Determine likelihood of erosion process. Allocate some probabilities to these (qualitative or quantitative).
� Given the storm regime, the fire size, its severity and the terrain what is the likelihood of responses in 3.
� Qualitative categories may be very unlikely (1: 10 000 chance), possible (1:1000 chance), highly probable (1:100) and almost certain (more than 1:10 chance). Use a risk framework which is consistent with other decision-‐making processes within the agency.
� Quantitative approaches may be used when detailed information on post-‐fire erosion responses is available.
� The assessment can be made using just terrain attributes (eq. 2; data at 90 m resolution made available through this project), or more ideally it can made using a combination of local data and erosion modelling. For planning fuel reduction burns the metric of erosion potential (eq .2) can be used to determine the relative risks within a catchment where planned burns are scheduled. This approach of datelining relative risks can also be used in a bushfire setting, although the likelihood of erosion events also depends on fire severity. If there is information available on the impact of fire severity on erosion, the LS factor can be adjusted based on fire severity mapped from satellite (e.g. Sheridan et al. 2009 or it can be incorporated into the RUSLE framework by adjusting the soil and cover factors in the equation (e.g. Rulli et al. 2013).
6. Plot in risk matrix and determine risk level.
� Terminology for likelihood, consequence and risk should be consistent with that used elsewhere in the decision-‐making processes.
� The information used to inform the risk assessment should be continuously updated with new knowledge and modelling capabilities.
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Strategies for risk mitigation are split into two sections: i) before planned fire; and ii) after bushfire 7.1.1 Prescribed fire Risk mitigation – fire operations
� Schedule burns in high risk areas in high value catchments over multiple years. � Promote patchy burns in steep terrain. Unburnt patches should be in the order of 10-‐100
metres. Patchiness is most effective when distributed throughout the source areas. Regular patches are more effective than a single buffer.
� Avoid burning in steep converging headwaters (1st-‐order basins, usually <200 ha) above high value assets. These parts of the landscape are prone to threshold driven shifts in erosion (i.e. channel initiation and evacuation of stored sediment in convergent headwaters).
� Unburnt buffers along drainage lines can be effective for most rainfall events, although their capacity to reduce sediment delivery to streams is likely to be exceeded during intense rainfall.
Monitoring and evaluation
� Post fire evaluation of hill slope erosion (e.g. Morris et al. 2013) can be used to build database to help inform future risk assessments. These qualitative assessments can be carried out opportunistically after rainfall events or as routine evaluation (e.g. one year after the burn). Qualitative erosion assessment can be quick and they can be carried out alongside other post-‐fire monitoring and evaluation protocol (fire severity, fauna and vegetation).
� More critically, a change in the rate of application of planned burns (recently set to 5%) should be accompanied with rigorous monitoring schemes for detecting trends in soil physical and chemical properties over time, in a similar way that fauna and flora are being monitored. Organic matter, nutrient levels, seed banks and soil microbial activity are critical components of forest ecosystems. Soil monitoring in areas of different erosion potential help capture the overall effect of fire regimes on forest ecosystems.
� High value catchments could be used as more intensive experiment for determining the long term effects of burning on sediment transport and water quality, although this would require significant investments in infrastructure for sampling and measuring sediment concentration and discharge in streams or rivers.
7.1.2 Bushfire Post-‐bushfire response
� Information on topography (DEM) and fire severity are nearly always available following bushfire. These can be used to evaluate erosion risk by following the steps outlined in section 7.1 using general approaches for modelling erosion (Rulli et al. 2013) or specific models developed for local conditions (Sheridan et al. 2009).
� These risk assessments should inform decisions regarding mitigation. � Examples of post-‐fire mitigation includes hill slope erosion control, preparing alternative
water supplies and limiting access to recreational areas and roads at risk of flash flooding or debris flows.
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8 Recommendation for future research priorities Landscapes are highly variable in terms of fire impacts on erosion. Some regional trends have emerged from the analysis presented in this report. Regions of ACT, Victoria and NSW fall into some of the highest risk categories in terms of the fire, storm and topographic controls (Figure 8). These regions also have the strongest knowledge base. There is considerable potential for fire to cause erosion in catchments near Hobart, yet very little is known about fire and erosion processes in this region. Local variation within regions can be large and site specific research on erosion is required to improve the knowledge base for quantitative risk assessments in various regions. Studies on post-‐fire erosion should therefore be carried out opportunistically when bushfire provides opportunities for obtaining parameters and data to improve modelling capacity. Common to all the fire prone regions is the lack of an integrated modelling approach for determining the net impact of a fire regime (including bushfire and planned fire) on the treatability of the water that is sourced from forested catchments. Key questions are:
� How can fire/land managers work with water supply agencies to develop plans that optimise prescribed burns (scheduling and operations) to achieve reduced risk of bushfire while also minimising the risk to water supply? Regular application of prescribed fire in water supply catchments means that there is some increased risk of water contamination in the short-‐term, but this increase in risk may be offset by the reduced risk of bushfire-‐related impacts in the future.
� What is the landscape scale effect of having large areas consistently exposed to higher erosion rates? For large catchment areas the increased application of planned burns means that some proportion of the catchment is in some state of elevated erosion potential. It is unclear how these impacts play out in terms of water quality and sediment transport at larger scales where patchiness within burns, their frequency, size and density (burns per area per time) become important.
� How does the size of burned areas, their severity and their frequency influence water quality and sediment transport to reservoirs?
Developing tools for optimizing burns in high value water catchments is high priority goal that would enable fire/land managers to carry out prescribed burns with the long-‐term strategy to reduce bushfire risk while maintaining the capacity of catchments to deliver drinking water at minimal cost to the water supply agencies. The development of such tools is currently constrained by a major gap in research in which there are currently no spatially explicit erosion models that evaluate the impact of fire regimes on water quality. Recent developments in fire modelling, however, demonstrate that it is becoming increasingly feasible to explore what fire regimes emerge under different climate and management scenarios and what the implications may be for land managers (Bradstock et al. 2012; Collins et al. 2015). When applied to erosion processes in a water supply catchment, this type of modelling approach would enable land and water managers to evaluate the cost and benefits of different fire management scenarios, taking into account both the operational and strategic elements of the fire management.
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Operations may be optimised so that highly sensitive (steep and erodible) areas of a water supply catchment are given special consideration during prescribed burns in terms of the overall area that is treated or the manner in which it is treated. For example, it may be important to know if there is some benefit in scheduling burns as multiple smaller burns every year, rather than a single large burn every second year. Additionally, where do land/fire managers have the most leverage in terms of minimising impacts? Is it by modifying the size and frequency of burns within a catchment or is it by modifying the lighting pattern within burns? What are the cost and benefit of different management scenarios in terms of water quality impacts, the resources needed to carry out the burns, and the overall reduction in bushfire risk (the high level objective of planned burning)? A model that incorporates planned and unplanned fire as two processes that combine to produce water quality risk requires parameters that describe the fire regime itself, as well as the erosion processes that emerge as a result of different burn outcomes (severity and patchiness). In most catchments, the parameters required to drive such a model are lacking. However, by focusing the model development around regions where the parameters and modelling capacity are available, it is possible to begin to explore how fire management can be optimised to minimise water quality impacts using the most cost-‐effective (or efficient) solutions. The result from this type of modelling approach is site specific in terms of the absolute values that the model produces. The trends and patterns that emerge however can be generalised more broadly and used to guide management activities outside the exact conditions for which the model was parameterised. Once the modelling framework is in place, there will be opportunities to apply the model to new regions by incorporating more site specific information on local erosion processes. Another important gap is the lack of knowledge on how landscapes vary in terms of their susceptibility to soil degradation as a result of frequent fire. Most studies on soil carbon and nutrients in fire-‐prone forests have been carried out in flat terrain where there is little potential for erosion. In mountainous terrain, there may be considerable variation in how soils (and hence vegetation) respond to changes in fire regimes. Developing robust monitoring systems for quantifying these potential effects is important when arguing for a marked shift in the sale of land management interventions, such as the 5% target currently being rolled out across the south and east coast of Australia. The soil is a critical component of the ecosystem and the effects of burning on the soil should be quantified over time as part of routine-‐based monitoring, alongside the monitoring of flora and fauna which is already taking place in most jurisdictions.
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Appendix 1
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Figure 5. LS factor for some water supply catchments near Perth (Helena and Canning Reservoirs)
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